As introduced in Section. 2, the generator matrix of the FTN system is a Toeplitz matrix, which follows a convolutional structure. To explore the convolutional structure of the FTN signaling, we propose to employ a simplified convolutional NN (CNN) to be performed as the NN FN to assist the SPDA [1]}, [2]}, [3]}.
CNNs are widely used in image recognition systems [1]}.
Traditional CNNs usually involve several convolutional layers (Conv) and max-pooling layers.
The convolutional layer performs the convolution operation of the filters (kernels), where the filters convolve and stride over the input. The max-pooling layer performs downsampling to reduce the spatial size of the convolved features.
A dense layer is appended after the max-pooling layer to provide possibly nonlinear functions [1]}.
In [2]}, a pure CNN based detection algorithm was proposed, where both the max-pooling layers and the dense layer are removed to reduce the training complexity, but a large number of convolutional layers and filters are kept.
